What OCR is and how AI reads invoices and documents

OCR has been around for decades, but on its own it returns a wall of text. What is new is the combination with AI models, including multimodal ones, which do not just read the characters but understand the document: this is the order number, this is the delivery date, this is the total.

This makes it possible to automate the reading of delivery notes, orders, foreign invoices and handwritten forms, with a person checking only the uncertain cases.

An example in an SMB

A transport company receives delivery documents photographed by its drivers. A system with OCR and AI reads each photo, extracts the recipient, whether a signature is present or missing, and any notes, and updates the shipment. Photos that can't be read go into a queue for the office.

The most common mistakes

• Not planning for a check on the uncertain cases: a misread number in an amount is expensive.
• Starting from very poor quality scans without improving how you collect them first.
• Assuming OCR understands structure: for tables and forms you need a model that can interpret them.

Why it matters to you

Many SMBs still have someone copying data by hand from paper documents or PDFs into their management software. It is slow work, full of typing errors. An automatic reading system does not remove the checking, but it moves it: the person verifies the exceptions instead of typing everything in.

All the AI terms explained simply are in the glossary.